Fractional Calculus · Oscillator Hardware

Athanor Alchemy

The Hardware is the Wave

Fractional Calculus Oscillator-Based Computers

Hardware that treats oscillation, continuous time, and fractional-order dynamics as native computational primitives — from software emulation to standalone analog chipsets.

A technology company of sNoise Research Laboratory

ATHANOR

Alchemy

Interactive

See the Principle in Motion

Three demonstrations of oscillator-based computation and the Genesis Unity Operator — the transfer function at the core of Fractional Scaling Digital Signal Processing.

1 · Coupled Oscillators

Click or drag to seed oscillators. Nearby nodes couple through a Kuramoto interaction. When the order parameter R rises, the field phase-locks — the physical substrate of the computation.

CLICK / DRAG TO SEED

N=0 · Order R=0.00 incoherent

2 · Phase Relationships & Interference

Two sources with adjustable phase. Constructive and destructive interference is a visual analogy for phase as a computational degree of freedom — the same degree of freedom von Neumann proposed for oscillator-based computers in 1954.

0.00π

3 · Genesis Unity Operator

Apply H(s) = 1 / sβ/2 in the complex frequency domain. Positive β integrates (memory, smoothing); negative β differentiates (change, roughening). Every magnitude response pivots at the Magnitude Transition Frequency, independent of order.

2.00

Gold trace is the filtered output; muted trace is the input. Right panel: log-log magnitude with the MTf pivot marked.

The Principle

From Oscillation to Computation

Oscillator-based computing was first explored in the 1950s. Fractional calculus supplies the mathematical language that makes continuous-time, memory-bearing dynamics practical in modern hardware.

01

Oscillator Foundations

Physical oscillators form a responsive substrate whose phase, amplitude, and coupling can encode and transform information.

02

Fractional-Order Dynamics

Fractional calculus introduces controllable memory and richer continuous-time behavior beyond classical integer-order models.

03

Hardware Realization

The principle is embodied in architectures designed for repeatability, scalability, and direct interaction with physical signals.

04

System Performance

Coupled dynamics deliver measurable capability for demanding computational and signal-processing workloads.

Platform

A Calculus of the Operators

FSDSP operationalizes fractional calculus in the complex Laplace domain. A single operator — the Genesis Unity Operator — performs integration, differentiation, and every fractional order between them by changing one parameter.

GENESIS UNITY OPERATOR

H(s) = [ K / sβ/2 ]æ

β · scaling exponent
Sign and magnitude set the order: positive β integrates, negative β differentiates, and β = 0 transmits.
æ · altitude exponent
Independent magnitude and phase-tension control across the spectrum, or at a single frequency.
MTf · unitary pivot
At f = 1/2π the operator is unity for every β — a stable geometric reference frame.

FSDSP Logic Gates

Continuous-wave equivalents of digital gates, driven by operator inputs (β, æ, K) rather than binary state. Cascaded into a Universal Machine Code.

FOST & SQG

Fractional Orthogonal Superposition interrogates custom frequencies beyond FFT bins. Symmetric Quadrant Generation synthesizes drift-free basis functions.

mFOPID / FSC

Multiplicative fractional-order control in the frequency domain. Proportional, integral, and derivative terms collapse into a Unified Fractional Operator.

HOFE & FCST

Orthogonal fractional encoding and cylindrical spatial multiplexing — stacking independent streams on a single carrier via phase geometry.

Phase-Coherent FC-AI

Deterministic classification by Boolean phase-lock rather than statistical backpropagation. Scales from edge chips to orchestrated expert matrices.

FC-OBC Substrates

Software, FPGA/ASIC, hybrid PCIe accelerators, and standalone analog arrays — LC tanks, memristors, CMOS rings, photonics, spin-torque oscillators.

Applications

What This Enables

Fractional-calculus oscillator-based approaches open new design space across multiple domains — wherever phase, memory, and resonance carry the information.

Artificial Intelligence

Hardware primitives that leverage continuous and fractional-order dynamics for learning and inference — including hallucination-resistant resonant classifiers.

Scientific Computing

Physical modeling and continuous-system problems that benefit from native dynamical hardware rather than integer-order discretization.

Signal & Wave Processing

Complex time-varying signals where phase, memory, and resonance carry primary information — beyond the Heisenberg–Gabor compromise of the FFT.

Control Systems

Fractional-order control architectures with richer memory and gain-invariant iso-damping for flight, robotics, and structural actuation.

Edge & Embedded

Signal-native computation placed closer to sensors and real-world environments, including zero-CPU logic arrays that compute by interference.

Advanced Sensing

Systems that extract structure from noisy or fractional-order natural processes — meteorological, acoustic, biomedical, and kinematic.

Heritage

A Long Arc, Made Practical

In 1954 John von Neumann patented an architecture for computation using the phase relationships of oscillators rather than binary voltage levels (U.S. Patent 2,815,488). Early implementations demonstrated the concept but were constrained by the analog technology of the time — and by the lack of a mathematics that could stabilize nonlinear fractional dynamics without phase ripple.

Decades later, fractional calculus and Fractional Scaling Digital Signal Processing supplied that missing foundation. sNoise Research Laboratory’s issued patents made continuous and fractional-order dynamics computationally tractable at scale, first as digital filters and control systems, then as a universal operator language.

Today

Athanor Alchemy focuses on the hardware realization of fractional-calculus oscillator-based computers — turning the algorithmic foundations developed at sNRL into physical systems.

Visit sNoise Research Laboratory
  1. 1954

    von Neumann OBC

    Phase of an oscillating signal as a computational primitive.

  2. 2013

    Dissertation

    Fractional Bode analysis of self-affine natural time series.

  3. 2017–20

    FSDSP Patents

    Four issued U.S. patents on fractional scaling filters and FOCS.

  4. 2026

    Omnibus

    Universal Machine Code, FC-OBC, and phase-coherent FC-AI — pending.

Intellectual Property

Issued Foundation

Athanor Alchemy is built on issued U.S. patents held by sNoise Research Laboratory, with an omnibus provisional covering the Universal Machine Code and oscillator-based computing embodiments.

  • US 9,740,662 B2 Fractional Scaling Digital Filters and the Generation of Standardized Noise and Synthetic Data Series Aug 22, 2017
  • US 10,164,609 B2 Fractional Scaling Digital Signal Processing Dec 25, 2018
  • US 10,169,293 B2 Fractional Scaling Digital Filters and the Generation of Standardized Noise and Synthetic Data Series Jan 1, 2019
  • US 10,727,813 B2 Fractional Scaling Digital Signal Processing Jul 28, 2020
  • Omnibus Provisional Operationalization of Fractional Calculus via FSDSP and FOCS for Universal Machine Code, FC-AI, and FC-OBC May 22, 2026 · pending

Inventor: Jeffrey R. Smigelski, Ph.D. · See the sNRL Patents page for details.

The next computational material

The hardware is the wave.
The next era of computing starts here.

Athanor Alchemy is building the physical systems that make fractional-calculus oscillator-based computation real.